In Drone-vs-Bird Detection Challenge in conjunction with the 4th International Workshop on Small-Drone Surveillance, Detection and Counteraction Techniques at IEEE AVSS 2021, we proposed a YOLOV5-based object detection model for small UAV detection and classification. YOLOV5 leverages PANet neck and mosaic augmentation which help in improving detection of small objects. We have combined the challenge dataset with one of the publicly available UAV air to air dataset having complex background and lighting conditions for training the model.

Computational Analysis and Acceleration Research Group (CARG)
Biomedical and UAV related research
- Ottawa, Ontario, Canada
- University of Ottawa
- Google Scholar
- Github